Comprehension about the behavior of the Planet Boundary Layer (PBL) is an important factor in several fields, from analysis about air quality until modeling. However, monitoring the PBL evolution is a complex problem, because few instruments can provide continuous atmospheric measurements with enough spatial and temporal resolution. Inside this scenario lidar systems appear as an important tool, because it complies with all these capabilities- However, PBL observations are not a direct measure, being necessary to use complex mathematic algorithms. Recently, wavelet covariance transforms have been applied in this field. The objective of this work is to compare the performing of distinct types of algorithms: a structured on Haar wavelet and other based on first derivative of Gaussian and Mexican Hat wavelets, and the results were compared with two Hysplit modelling. For this aim, two campaigns were carried out. From the results were possible to infer that both algorithms provide coherent results as the expected, but the Haar algorithm separates the sub-layers more efficiently, so it is the most appropriate to complex situations.